从字节到偏见：调查大型语言模型的文化自我认知
From Bytes to Biases: Investigating the Cultural Self-Perception of Large Language Models
AI总结：
本文利用 GLOBE 项目的价值观问题测试 ChatGPT 和 Bard，发现其文化自我认知最贴近英语国家及持续经济竞争力国家，并强调识别 LLM 文化偏见以避免偏见循环的重要性。
摘要：
大型语言模型（LLM）能够与人类进行听起来自然的对话，展示出前所未有的信息检索和自动化决策支持能力。它们已经颠覆了人机交互以及企业运营方式。然而，基于生成式人工智能（GenAI）的技术众所周知会产生幻觉、传播错误信息，并表现出由其训练所用海量数据集引入的偏见。现有研究表明，人类可能会无意识地内化这些偏见，即使在停止使用这些程序后，偏见仍可能持续存在。本研究通过使用源自 GLOBE 项目的价值观问题向 ChatGPT（OpenAI）和 Bard（Google）提问，探索 LLM 的文化自我认知。研究结果显示，它们的文化自我认知与英语国家以及以持续经济竞争力为特征的国家的价值观最为一致。认识 LLM 的文化偏见并理解其运作方式对社会所有成员都至关重要，因为人们不希望人工智能黑箱在人类中延续偏见，而人类反过来可能会无意中创建和训练更具偏见的算法。
英文摘要：
Large language models (LLMs) are able to engage in natural-sounding conversations with humans, showcasing unprecedented capabilities for information retrieval and automated decision support. They have disrupted human-technology interaction and the way businesses operate. However, technologies based on generative artificial intelligence (GenAI) are known to hallucinate, misinform, and display biases introduced by the massive datasets on which they are trained. Existing research indicates that humans may unconsciously internalize these biases, which can persist even after they stop using the programs. This study explores the cultural self-perception of LLMs by prompting ChatGPT (OpenAI) and Bard (Google) with value questions derived from the GLOBE project. The findings reveal that their cultural self-perception is most closely aligned with the values of English-speaking countries and countries characterized by sustained economic competitiveness. Recognizing the cultural biases of LLMs and understanding how they work is crucial for all members of society because one does not want the black box of artificial intelligence to perpetuate bias in humans, who might, in turn, inadvertently create and train even more biased algorithms.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
